Bias Compensation of Recursive Least Squares Estimate in Closed Loop Environment

نویسندگان

  • K. Ikeda
  • Y. Mogami
  • T. Shimomura
چکیده

In this paper, an asymptotic bias of the recursive least squares (RLS) estimate in the closed loop environment is analyzed and its compensation method is proposed under the assumption that the noise is white. Namely, a bias compensated RLS method in the closed loop environment based on output error (OE) model is proposed. A posteriori error is also analyzed for the estimation of the noise variance.

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تاریخ انتشار 2008